I re-did the DIA analysis from the beginning. This time I only used settings used by Emma in her Skyline document that she sent me.
I think I must have done something better this time around, because a lot of the chromatograms are looking much better. Now I will do the error rate calculation and finally get into the data analysis after that.
Error rate assessment
Skyline doesn’t always do the best job of identifying peaks (where transitions align, meaning that the peptide is real and can be identified). So, error rate has to be calculated.
In order to do this, I will look at ~100 randomly selected peptides and give them a rating of “1” or “0”.
A rating of “1” will only be applied if the following three conditions are met:
- The peak selected is likely a real peptide (either has an ID and/or the transitions align well)
- The peak boundaries encompass the peak well
- The same peak is at about the same retention time and is selected across all replicates (in my case, the four replicates)
A rating of “0” will be given if not all three conditions are met.
I’m not sure if I should figure out a way to identify which condition wasn’t met.
from grace-ac.github.io http://ift.tt/2FJw0lJ
Another classification revision
I met with Brent last week to go through my histology classifications. He recommended that I review the some specimens with the microscope.
Retaking histology images
I read another paper he recomended, Coe 1932, to understand the differences between primary ovogonia and spermatagonia. I read the paper, as well as some guides on tissue types from Carolyn Friedman, then had some dedicated microscope time. Here are the revised classifications and some notes. The classifiation spreadsheet can be found here, and the new images I took can be found here for pre-experiment sampling and here for post-experiment sampling. Shoutout to Grace for helping me set up the iPhone + microscope contraption!
- Gigas_02: Stage 1 Female. Need to verify that it’s not male. Ovogonia are closer to the walls of the acini, so I’m pretty sure it’s female
- Gigas_04: Same as above
- Gigas_05: Looking at the primary sex cells, they’re farther away from the walls of the acini. This may be male? There’s also a chance that I didn’t find any acini and I’m looking at the digestive gland or intestines instead. Need to clarify with Brent.
- Gigas_06: Stage 1 Female
- Gigas_07: No acini structure, so Stage 0
- Gigas_08: Same as above
- Gigas_10: Same as above
- Gigas_15: Found some spermatazoa! No acini structure, so it’s a spent oyster. Stage 4 Male!
- Gigas_18: No acini structure, so Stage 0
- Gigas_20: Same as above
- 4-T3: Same as above
- 5-T3: Same as above
- 9-T2: Same as above
- 10-T3: Same as above
- 12-T6: Spermatazoa but no acini structure. Stage 4 Male
- UK-03: No acini structure, so Stage 0
- UK-05: Spermatazoa but no acini structure. Stage 4 Male
Gonad maturation analyses
Not much changed from my previous analysis. Sex is still the only factor that explains differences in maturation. However, I now have different mature and immature classifications between treatments. None of my low pH animals were mature. In my ambient pH treatment, six individuals were immature and four were mature. When I was building my binomial GLM using stepwise regression methods, I got a p-value of 0.03 when I had a Mature ~ Treatment model. However, Sex was a more significant factor, so I added that in first to create my base model. When I used
add1 to identify which covariates to add, none of them were significant! Guess I don’t have to change the story in my NSA presentation.
from yaaminiv.github.io http://ift.tt/2HwqCTo
Emma came over and took a look at my 2015 Oysterseed Skyline DIA Analysis file. She said that it doesn’t look right and that I should re-do it and make sure I’m following Laura and Yaamini’s settings and/or comparing it to the Skyline document that she sent me.I looked at it a little today, but am just very confused. I have looked at the tutorial from SKyline, and followed the protocols, but I still don’t understand what’s going on. I’ll give it another go tomorrow morning before lab meeting.
Today I started isolating RNA. I started out with 9 samples from infected, ambient crabs. Here is the spreadsheet of all the samples that I will use for RNA isolation (if I’m unnsuccessful with any, there are many other samples I could use).
from grace-ac.github.io http://ift.tt/2InQGS3